Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances

被引：419

作者：

Kelejian, Harry H. ^{[1
]}

Prucha, Ingmar R. ^{[1
]}

机构：

[1] Univ Maryland, Dept Econ, College Pk, MD 20742 USA

来源：

JOURNAL OF ECONOMETRICS | 2010年 / 157卷 / 01期

基金：

美国国家科学基金会;

关键词：

Spatial dependence; Heteroskedasticity; Cliff-Ord model; Two-stage least squares; Generalized moments estimation; Asymptotics; FINITE-SAMPLE PROPERTIES; GMM ESTIMATION; SPILLOVERS; 2SLS;

D O I：

10.1016/j.jeconom.2009.10.025

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This study develops a methodology of inference for a widely used Cliff-Ord type spatial model containing spatial lags in the dependent variable, exogenous variables, and the disturbance terms, while allowing for unknown heteroskedasticity in the innovations. We first generalize the GMM estimator suggested in Kelejian and Prucha (1998, 1999) for the spatial autoregressive parameter in the disturbance process. We also define IV estimators for the regression parameters of the model and give results concerning the joint asymptotic distribution of those estimators and the GMM estimator. Much of the theory is kept general to cover a wide range of settings. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：53 / 67

页数：15